Article
Engineering, Industrial
Ufuk Bahceci, Temel Oncan
Summary: In this study, customized Mixed Integer Linear Programming (MILP) formulations were developed for the Order Batching Problem (OBP) for the first time, considering various routing policies. A novel picker routing policy named mixed policy was introduced. Extensive computational experiments were conducted to analyze the impact of different routing and storage policies under various operating conditions, leading to several managerial insights.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Mengge Yuan, Ning Zhao, Kan Wu, Zhibin Chen
Summary: This paper studies the drug storage location assignment problem of automated drug dispensing machines and proposes an assignment strategy based on Jaccard similarity coefficient and drug demand frequency, aiming to improve space utilization and efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Economics
Yanling Zhuang, Yun Zhou, Elkafi Hassini, Yufei Yuan, Xiangpei Hu
Summary: This paper investigates the rack storage and robot assignment problem in robotic mobile fulfillment systems with the goal of minimizing the makespan. A matheuristic decomposition approach is proposed and tested, demonstrating good performance for both large-scale real-world cases and small-scale synthetic instances.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Transportation Science & Technology
Michele D. Simoni, Matthias Winkenbach
Summary: The meal delivery business has been revolutionized by online food delivery platforms since the early 2010s. These platforms match couriers to meal orders in order to provide an efficient and reliable service. This study proposes an algorithm that uses clustering and graph-based approach to batch and assign orders, and it is combined with advanced policies for further optimization.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Industrial
Kai Zhang, Chuanhou Gao
Summary: Order picking is the retrieval process of ordered products from storage locations in warehouses. In picker-to-parts systems, multiple customer orders can be assigned to a single picker, requiring routing decisions for the picking tour. Integrated batching and routing have been found to enhance the efficiency of order picking operations compared to solving the problems separately. This study investigates the mathematical programming formulation of this integrated problem and presents improved formulations and computational results for various warehouse configurations.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Sergio Gil-Borras, Eduardo G. Pardo, Antonio Alonso-Ayuso, Abraham Duarte
Summary: The study focuses on the Online Order Batching Problem with Multiple Pickers (OOBPMP) and proposes a multi-start procedure hybridized with a Variable Neighborhood Descent metaheuristic to solve the problem. Empirical comparisons on well-known instances from the literature show that the proposed method performs significantly better than previous methods.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Dapei Jiang, Xiangyong Li
Summary: This paper investigates the order fulfilment problem in online retailing environment, proposing a mixed-integer linear programming model and a decomposition-based approach, with extensive experiments to verify effectiveness. Furthermore, managerial insights are provided on how this approach could reduce order transfer operations at distribution centers and optimize fulfilment expenses.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Industrial
Sen Xue, Chuanhou Gao
Summary: This paper highlights the relationship between picking and packing processes in warehouse management and presents a mixed-integer programming model for optimization. To address model complexity, a statistical-based framework is proposed for generating approximate models and selecting the optimal one. Experimental results demonstrate the effectiveness of the proposed framework and hybrid algorithm.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
K. L. Keung, C. K. M. Lee, P. Ji
Summary: This paper discusses the value creation of utilizing robotic process automation in robotic mobile fulfillment system under cloud-based Cyber-Physical Systems, proposing a data-driven approach for storage location assignment problem and improving operational efficiency.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Automation & Control Systems
Xiang Shi, Fang Deng, Miao Guo, Jiachen Zhao, Lin Ma, Bin Xin, Jie Chen
Summary: This article studies the order picking optimization problem in a robotic mobile fulfillment system and proposes a fulfillment-focused simultaneous assignment method. The method consists of two stages, compression and simultaneous assignment, and utilizes specific algorithms and strategies to obtain high-quality solutions.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Management
Ivan Zulj, Hagen Salewski, Dominik Goeke, Michael Schneider
Summary: The study focuses on an AMR-assisted picker-to-parts system in warehouses, aiming to minimize the total tardiness of customer orders by partitioning the warehouse into zones, using AMRs to support order pickers, and optimizing the travel and walking speed ratios between AMRs and order pickers. Increasing the speed ratio is found to be more effective in reducing total tardiness compared to increasing the AMR fleet size.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Babiche Aerts, Trijntje Cornelissens, Kenneth Soerensen
Summary: The research focuses on the joint order batching and picker routing problem (JOBPRP) in a warehouse environment, using a two-level variable neighborhood search (2level-VNS) metaheuristic algorithm. Comparing different batching criteria, it is concluded that the minimum aisles criterion is more suitable for JOBPRP in warehouse contexts.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Engineering, Manufacturing
Kazunori Maruyama, Takashi Yamazaki
Summary: This study proposes a co-optimization method using order batching and storage location assignment to improve the efficiency of order picking in stock-type warehouses at production sites and supply chains. The numerical experiments validate the effectiveness and efficiency of the co-optimization method in controlling and executing local optimization techniques based on order characteristics.
JOURNAL OF ADVANCED MECHANICAL DESIGN SYSTEMS AND MANUFACTURING
(2022)
Article
Computer Science, Artificial Intelligence
Cagla Cergibozan, A. Serdar Tasan
Summary: The order batching problem is a critical problem in warehouse order picking process. This study aims to develop fast and effective metaheuristic approaches to solve this problem, and the proposed algorithms are validated through numerical tests and a real case study, demonstrating their practicality and usefulness.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Article
Operations Research & Management Science
Jintao You, Canrong Zhang, Zhaojie Xue, Lixin Miao, Bin Ye
Summary: The research focuses on Local Container Drayage Problem (LCDP), proposing a robust bi-objective optimization model to balance operational cost and robustness. An Ant Colony Optimization (ACO) scheme is employed to search for feasible solutions, with numerical experiments validating the effectiveness and efficiency of the proposed models and methods.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Management
Xi Xiang, Changchun Liu
Summary: The study investigates berth allocation planning problem at container terminals considering uncertain operation time, and formulates a data-driven expanded robust optimization model to minimize the total cost of deviations. A K-means clustering is used to construct the uncertainty set, and a column-and constraint generation algorithm is presented to solve the model. Experiment results demonstrate that the proposed model can effectively guarantee performance and avoid over-conservatism of traditional robust optimization models.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Mathematics, Interdisciplinary Applications
Yangcan Wu, Lixin Miao
Summary: Uncertainty is a key aspect of seaside operations in container terminals, and this paper proposes a method to insert buffers into baseline berth plans to improve schedule stability, increasing operational flexibility and addressing service priority impact.
DISCRETE DYNAMICS IN NATURE AND SOCIETY
(2021)
Article
Management
Xi Xiang, Changchun Liu
Summary: The study addresses the integrated berth allocation and quay crane assignment problem in container terminals, introducing robustness index and weighted max penalty function to propose an efficient solution. Numerical experiments demonstrate the method's advantages in handling uncertainties and excellence in managing a large number of vessels and cranes.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Engineering, Industrial
Liu Changchun, Xiang Nengjie
Summary: This paper studies a flexible job shop problem with parallel machines, aiming to minimize the maximum flow time. Based on problem characteristics, a property is discovered to reduce the solution space dimension. A series of algorithms are proposed to solve problems of different scales, and computational experiments demonstrate their effectiveness and efficiency.
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING
(2021)
Article
Management
Kanglin Liu, Changchun Liu, Xi Xiang, Zhili Tian
Summary: This paper focuses on locating testing facilities to meet varying demand caused by pandemics. A two-phase optimization framework is proposed to locate facilities and adjust capacity during emergencies. Online convex optimization and online gradient descent algorithms are used to solve the problem. A case study verifies the effectiveness of the framework.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Automation & Control Systems
Xi Xiang, Changchun Liu, Loo Hay Lee, Ek Peng Chew
Summary: This article analyzes the impact of container flows on the performance of automated container terminals, taking into account factors such as traffic congestion, task allocation, and container batch arrivals. The system capacity, resource allocation, and layout design are optimized through theoretical analysis and numerical experiments, providing insights for port capacity planning and resource optimization.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Xi Xiang, Tao Fang, Changchun Liu, Zhi Pei
Summary: This study proposed an optimization method for a robust service network design problem, balancing objective value and penalty violation with penalty limit constraint and robustness index. A decomposition method was introduced to solve the problem, with numerical results demonstrating the efficiency of the algorithm. The robust optimization approach was validated using real data, resulting in a robust parcel delivery network design with satisfactory out-of-sample performances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
Xinye Hao, Changchun Liu, Maoqi Liu, Canrong Zhang, Li Zheng
Summary: This study addresses the optimization problem in furniture manufacturing through problem formulation and iterative heuristic algorithm. The researchers have successfully found efficient and stable solutions, leading to significant reduction in costs and waste in practical scenarios.
Article
Engineering, Manufacturing
Maoqi Liu, Li Zheng, Changchun Liu, Zhi-Hai Zhang
Summary: We study the problem of product design decisions, where a decision maker chooses product features from a set of possible options. We focus on two commonly studied objectives in this field, specifically, the share of choice (SOC) and buyers' welfare (BW). We propose a distributionally robust optimization (DRO) SOC maximization model and a winsorized BW maximization model to generate robust solutions for the two objectives.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Engineering, Manufacturing
Ju Liu, Changchun Liu, Chung Piaw Teo
Summary: We propose a general framework for selecting candidate solutions in combinatorial optimization problems based on linear and additive random payoff functions. Through a two-stage distributionally robust model and a mixed 0-1 semidefinite program, we exploit the diversification effect to improve the chances of obtaining high payoff solutions. Furthermore, our model recovers the "evil twin" strategy in football pool betting under appropriate settings. We also address the computational challenges of scaling up our approach and provide a sequential optimization method based on compact semidefinite programming.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Automation & Control Systems
Xi Xiang, Loo Hay Lee, Ek Peng Chew
Summary: This study focuses on the multi-period dynamic integrated optimization problem in automated transshipment hubs, specifically berth allocation, quay crane assignment, and yard assignment problems. The authors propose a multi-objective model to maximize total revenue, saved time deviation, saved transportation distance, and service quality. They develop an efficient adaptive dynamic scheduling policy that balances the trade-offs between multiple objectives. Numerical experiments demonstrate the effectiveness of their approach compared to benchmark policies, offering solutions with a delicate balance between multiple objectives and bringing value to automated container terminals.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
